docstr: Return inv_delta_C which is needed to calculate T 
docstr_tok: ["Return","inv_delta_C","which","is","needed","to","calculate","T"]
code: def build_inv_delta_C_paddle(self, C):
      """Return inv_delta_C which is needed to calculate T"""
      F = self.F
      hat_eye = paddle.eye(F, dtype="float64")  # F x F
      hat_C = (
          paddle.norm(
              C.reshape([1, F, 2]) - C.reshape([F, 1, 2]), axis=2
          )
          + hat_eye
      )
      hat_C = (hat_C**2) * paddle.log(hat_C)
      delta_C = paddle.concat(  # F+3 x F+3
          [
              paddle.concat(
                  [paddle.ones((F, 1), dtype="float64"), C, hat_C],
                  axis=1,
              ),  # F x F+3
              paddle.concat(
                  [
                      paddle.zeros((2, 3), dtype="float64"),
                      paddle.transpose(C, perm=[1, 0]),
                  ],
                  axis=1,
              ),  # 2 x F+3
              paddle.concat(
                  [
                      paddle.zeros((1, 3), dtype="float64"),
                      paddle.ones((1, F), dtype="float64"),
                  ],
                  axis=1,
              ),  # 1 x F+3
          ],
          axis=0,
      )
      inv_delta_C = paddle.inverse(delta_C)
      return inv_delta_C
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  from paddle import nn, ParamAttr
  from paddle.nn import functional
  import numpy
label_desc: Use image node_id 5 for calling the GridGenerator obj's underlying member method code with example usage: obj.build_inv_delta_C_paddle(C) and returns: inv_delta_C